Source apportionment of polycyclic aromatic hydrocarbons in Lake Baikal water and adjacent air layer

Semenov, M. Yu.; Marinaite, Irina I.; Golobokova, L. P.; Khuriganova, O. I.; Ходжер, Т. В.; Semenov, Yuri M.

doi:10.1080/02757540.2017.1393533

Cited by 23 publications

(25 citation statements)

References 48 publications

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“…The DOC concentration in the lake water also increases (up to 2-4 mg/L) toward the mouths of inflow rivers [45,46] and decreases with increasing depth. The sum concentration of six PAHs in Baikal water rarely exceeds 4 ng/L, which is much less than that in tributary waters [21,42]. As in the case of DOC, this finding is due to the photo-and biodegradation processes that occur in the water in the lake.…”

Section: Chemical Composition Of Baikal Watermentioning

confidence: 85%

“…Thus, the amplitude of annual CRR oscillations depends on contaminant abundance, whereas the spatial CRR variability depends on water chemistry and presence of pollution sources. The absence of any meaningful spatial and temporal patterns of the PAH removal rate (Figure 3f) is probably because multiple point and nonpoint PAH emission sources and pathways drive the continuous release of PAHs into the river [21]. The removal of PAHs from water occurs through photo-and biodegradation, as well as through sorption on particulate matter and subsequent sedimentation [22].…”

Section: Elements Moderately Correlated and Uncorrelated With Docmentioning

confidence: 99%

“…Additionally, the self-purification of lake water with respect to biogenic elements [19] and heavy metals [20] can be assessed on the basis of changes in their concentrations in the water and suspended sediments with increasing distance from the Selenga delta. Organic matter (OM) sequestration in the lake results in qualitative and quantitative composition changes in waterborne polycyclic aromatic hydrocarbons (PAHs) in the onshore-offshore direction [21,22]. One mechanism of water purification from organic solutes such as PAH and OM is microbial degradation [22].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Self-Purification Capacity of Surface Waters in Lake Baikal Watershed

Semenov

Силаев

et al. 2019

Water

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The removal of trace metals (TM), dissolved organic carbon (DOC), mineral nitrogen (Nmin.), and polycyclic aromatic hydrocarbons (PAHs) from the water of Lake Baikal and its tributaries was evaluated. The contaminant removal rate (CRR) and the contaminant removal capacity (CRC) were used as water self-purification parameters. The CRR was calculated as the difference between contaminant mass flow rates at downstream and upstream gauging stations. The CRC was calculated as the quotient of the CRR and the change in water discharge between downstream and upstream gauging stations. Whether the CRR and CRC have positive or negative values depends on whether contaminant release or removal occurs in the water body. The CRR depends on the size of the water body. The lowest and the highest CRRs observed for Baikal were equal to −15 mg/s (PAHs) to −7327 g/s (DOC), whereas the highest PAH and DOC removal rates observed for Selenga River (the major Baikal tributary) in summer were equal to −9 mg/s and −3190 g/s correspondingly. The highest PAH and DOC removal rates observed for small tributaries were equal to 0.0004 mg/s and −0.7 g/s respectively. The amplitude of annual CRR oscillations depends on contaminant abundance. The highest amplitude was typical for most abundant contaminants such as Nmin. and DOC. In unpolluted sections of the Selenga River the highest rates of N and C removal (−85 g/s and −3190 g/s, respectively) were observed in summer and the lowest rates (4 g/s and 3869 g/s, respectively) were observed in the spring. The lowest amplitude was typical for PAHs and some low-abundance TM such as V and Ni. The highest summer rates of V and Ni removal were equal to −378 mg/s and −155 mg/s respectively, whereas lowest spring rates are equal to 296 mg/s and 220 mg/s. The intermediate CRR amplitudes were typical for most abundant TM such as Sr, Al, and Fe. The spatial CRR variability depends on water chemistry and the presence of pollution sources. The lowest (up to 38 g/s) rates of Nmin. removal was observed for polluted lower Selenga sections characterized by low water mineralization and high DOC concentrations. The highest rates (−85 g/s) were observed for unpolluted upper sections. Seepage loss from the river to groundwater was also recognized as an important means of contaminant removal. The CRC values depend mostly on water residence time. The DOC removing capacity value of Baikal (−26 g/m3) were lower than those of Selenga in summer (−35 g/m3) but higher than the CRCs of all tributaries during the other seasons (from 30 mg/m3 to −10 g/m3).

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Section: Chemical Composition Of Baikal Watermentioning

confidence: 85%

Section: Elements Moderately Correlated and Uncorrelated With Docmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessing the Self-Purification Capacity of Surface Waters in Lake Baikal Watershed

Semenov

Силаев

et al. 2019

Water

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“…The area is not densely populated (population density is 2.8 people per square kilometer); however, numerous anthropogenic emission sources are located in the Lake Baikal catchment. Some sources, such as pulp and paper mills, oil-fired and coal-fired central and residential heating boilers, wood stoves, and woodworking plants are located directly on the lake shore [43]. Other sources, such as aluminum plants, oil refineries, and asphalt plants, as well as numerous central and residential heating boilers, are located upwind from the lake along the Angara (the only Baikal outflow) and Selenga (a major Baikal tributary) river valleys [8].…”

Section: Sustainability 2020 11 X For Peer Review 3 Of 17mentioning

confidence: 99%

“…Organic tracers, such as polycyclic aromatic hydrocarbons (PAHs), are subject to oxidation by ozone or nitrogen oxides [36] or due to microbial degradation [37][38][39]. Changes in organic tracer values may also occur during the sampling process [40][41][42] or due to physicochemical [43,44] or biological [45] fractionation. Stable isotopes of light elements are more conservative than those of PAHs; however, they also can be biased due to mixing of element sources and biological fractionation [46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Using Si, Al and Fe as Tracers for Source Apportionment of Air Pollutants in Lake Baikal Snowpack

et al. 2020

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The aim of this study was to select chemical species characterized by distinctly different proportions in natural and anthropogenic particulate matter that could be used as tracers for air pollutant sources. The end-member mixing approach, based on the observation that the chemical species in snow closely correlated with land use are those that exhibit differences in concentrations across the different types of anthropogenic wastes, was used for source apportionment. The concentrations of Si and Fe normalized to Al were used as tracers in the mixing equations. Mixing diagrams showed that the major pollution sources (in descending order) are oil, coal, and wood combustion. The traces of several minor sources, such as aluminum production plants, pulp and paper mills, steel rust, and natural aluminosilicates, were also detected. It was found that the fingerprint of diesel engines on snow is similar to that of oil combustion; thus, future research of the role of diesel engines in air pollution will be needed. The insufficient precision of source apportionment is probably due to different combinations of pollution sources in different areas. Thus, principles for the delineation of areas affected by different source combinations should be the subject of further studies.

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Assessment of European and hybrid aspen clones efficiency based on height growth and removal percentage of petroleum hydrocarbons—a field trial

Salam

Mohsin

Rasheed

et al. 2020

Environ Sci Pollut Res

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Soils polluted by organic or inorganic pollutants are an emerging global environmental issue due to their toxic effects. A phytoremediation experiment was conducted to evaluate the extraction potential of three European aspen clones (R2, R3, and R4) and seven hybrid aspen clones (14, 27, 34, 134, 172, 191, and 291) grown in soils polluted with hydrocarbons (includes polycyclic aromatic hydrocarbons (PAH) and total petroleum hydrocarbons (TPH)). Height growth, plant survival rates, and .hydrocarbon removal efficiencies were investigated over a 4-year period at a site in Somerharju, Luumaki Finland, to assess the remediation potential of the clones. Hydrocarbon content in the soil was determined by gas chromatography and mass spectrometry. The results revealed that hybrid aspen clones 14 and 34 and European aspen clone R3 achieved greater height growth (171, 171, and 114 cm, respectively) than the other clones in the study. Further, the greatest removals of PAH (90% at depth 10-50 cm) and (86% at depth 5-10 cm) were observed in plot G15 planted with clone R2. Furthermore, the greatest TPH removal rate at 5-10 cm depth (C 22-C 40 , 97%; C 10-C 40 , 96%; and C 10-C 21 , 90%) was observed in plot 117 with clone 134. However, other clones demonstrated an ability to grow in soils with elevated levels of TPH and PAH, which indicates their tolerance to hydrocarbons and their potential capacity for phytoremediation of hydrocarbon-polluted soils. Our study suggests that European aspen and hybrid aspen clones could be used for the remediation of soils polluted with PAH and TPH.

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Source apportionment of polycyclic aromatic hydrocarbons in Lake Baikal water and adjacent air layer

Cited by 23 publications

References 48 publications

Assessing the Self-Purification Capacity of Surface Waters in Lake Baikal Watershed

Assessing the Self-Purification Capacity of Surface Waters in Lake Baikal Watershed

Using Si, Al and Fe as Tracers for Source Apportionment of Air Pollutants in Lake Baikal Snowpack

Assessment of European and hybrid aspen clones efficiency based on height growth and removal percentage of petroleum hydrocarbons—a field trial

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